A public Shopify app connecting a merchant's store to Kissmetrics, the customer-analytics platform. It captures storefront and checkout events automatically and pipes them into Kissmetrics' reporting suite — funnels, cohorts, paths, activity, revenue, A/B tests and SQL reports — so behaviour can be analysed at the individual-person level rather than the session level. Three tiers run $299–$999/month, scaling by event volume (2M → 10M), seats and populations. Launched 16 January 2026.
A public Shopify app connecting a merchant's store to Kissmetrics, the customer-analytics platform. It captures storefront and checkout events automatically and pipes them into Kissmetrics' reporting suite — funnels, cohorts, paths, activity, revenue, A/B tests and SQL reports — so behaviour can be analysed at the individual-person level rather than the session level. Three tiers run $299–$999/month, scaling by event volume (2M → 10M), seats and populations. Launched 16 January 2026.
The brief
The challenge, and how we approached it
01
The challenge
Shopify's native analytics reports sessions and orders; Kissmetrics reports people. Bridging the two means capturing every meaningful storefront and checkout event, resolving it to a persistent customer identity across visits and devices, and doing it with minimal merchant configuration — because the buyer at this price point is paying for insight, not an implementation project.
02
Our approach
Automated event capture on install: storefront and checkout events are instrumented without the merchant writing tracking code, using Shopify's checkout extension surface for the post-cart stage where most attribution breaks. Events map onto Kissmetrics' person-level model so journeys stitch across sessions, feeding funnel, path, cohort and revenue reporting rather than a separate in-app dashboard. Pricing tiers by event volume, seats and populations — so the integration scales with data throughput rather than store size, and reporting depth unlocks as merchants move up.
What we built
Six capabilities shipped for Dana's Bakery
Each one solves a specific part of the brief above.
ZIP-gated shipping
Real-time validation prevents invalid ZIP purchases from entering cart
Drop architecture
Pre-staged inventory with countdown, sold-out gates, and waitlist
Gifting flow
Message cards, recipient addressing, scheduled delivery, gift wrap
Perishable inventory
Daily inventory sync with cold-chain capacity constraints
Drop-day performance
Theme architecture handles 20× traffic spikes without latency
Recurring orders
Holiday subscription flow for repeat gifters
How it ran
10 weeks build, in four stages
Every engagement runs the same four stages, so you always know what happens next and what you owe us at each one.
Stage 1
Audit and scope
We review the current theme, apps and analytics, then write a fixed-scope SOW with named deliverables and a date.
Stage 2
Design and build
Work happens in a dev store on a Git-backed workflow. You get a preview link from week one, not a reveal at the end.
Stage 3
QA and launch
Cross-browser and device QA, redirect map, analytics verification, then a launch window agreed with you rather than dropped on you.
Stage 4
Hypercare
Fourteen to sixty days of included post-launch support while real traffic finds the edge cases.
The outcome
Where Dana's Bakery landed
Conversion is up 2.1× after the PDP rebuild, AOV is up 34% year-over-year thanks to gifting upsells, and drop days are now smooth — zero downtime across 12 drops in the past year.
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★
★
★
★
★
Every drop day was a stress event before. Now they're just a Tuesday. The team built us infrastructure we can actually grow on.
FounderKissmetrics
Tech stack
What this project runs on
The exact platform, services and integrations behind the build.
Commerce platform
Shopify Plus
Launchpad
Shopify Functions
Online Store 2.0
Engineering
Custom ZIP validator
Growth and operations
Klaviyo
ShipBob
More case studies
Other work worth reading
Long-form studies from the same team, with the numbers behind them.
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